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Keywords:

  • quality of life;
  • neoplasms;
  • second primary cancer;
  • survivors;
  • cancer

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

BACKGROUND.

Cancer survivors may develop additional cancers after their first diagnosis, but to the authors' knowledge the quality of life (QOL) consequences of a second cancer are not known. The current study assessed QOL and its correlates after a second cancer diagnosis.

METHODS.

QOL was compared between 487 survivors of second-order and higher-order primary cancer diagnoses, and a matched group of 589 survivors of a single cancer diagnosis. Outcome measures included standardized questionnaires that assessed depressive symptoms, perceived stress, vitality, post-traumatic growth, existential well-being, sexual adjustment, and global QOL.

RESULTS.

Survivors of multiple primary cancer diagnoses had significantly lower global QOL (t (792) = 5.42; P < .001), vitality (Student t test [t] (794) = 2.41; P < .01), and existential well-being (t (775) = 2.78; P < .01), and higher intrusive stress symptoms (t (775) = −1.93; P < .05). Controlling for demographic, medical, and trait-like psychosocial characteristics (eg, optimism and resilience), having multiple primary cancer diagnoses explained small, although significant, variances in global QOL (coefficient of determination [R2] = .04; P < .001), vitality (R2 = .01; P < .05), and existential well-being (R2 = .01; P < .05), with patients in the multiple primary cancer group faring worse on all of these measures.

CONCLUSIONS.

The results of the current study suggest that the typical survivor of multiple primary cancers experiences modest but lasting QOL deficits. Cancer 2007. © 2007 American Cancer Society.

For numerous reasons, survivors of a first primary cancer face an increased risk of developing future cancers. Genetic predispositions or cancer-causing behaviors may generate subsequent neoplasms, and long-term survivors may become prone to additional cancers as they age.1 Some cancer treatments give rise to iatrogenic tumor development, as when esophageal cancer arises from chest radiation for breast cancer.2 Finally, because medical advances have resulted in higher cure rates for many cancers, larger numbers of patients survive only to face later malignancies. For these reasons, second primary cancers are calculated to be the sixth most common cancer diagnosis.3 Cancer survivors comprise an estimated 16% of those diagnosed with a new cancer, which is > 4 times the population-based expected rates.4

Despite rising scientific interest in second primary cancers, to our knowledge the literature is silent concerning the psychosocial impact of a second primary cancer diagnosis. For example, the combined search terms “second primary” or “multiple primary” and “cancer” in both the PubMed and PsycINFO databases yield no quantitative or qualitative study regarding the psychosocial sequelae of multiple primary cancers.

Given the lack of data specific to subsequent primary cancers, cancer recurrence may provide a relevant comparison, despite the important differences between a cancer recurrence and a second primary cancer diagnosis. Recurrence, or the return of a previously diagnosed cancer, often indicates advanced disease, whereas an additional primary cancer is often diagnosed at an early stage due to the frequent monitoring that cancer survivors receive from their oncologists. Nonetheless, from the patient's perspective, dealing with cancer again, whether due to a recurrence or a new primary tumor, may be comparable.

Research suggests that patients with recurrent cancer cope in ways similar to their first cancer diagnosis. Controlled comparison studies have found little difference in overall distress or global quality of life (QOL) between individuals who experience a first cancer diagnosis and those who experience nonmetastatic cancer recurrence, although recurrence can be associated with increased cancer-specific stress.5–7 These patients may have pre-established support networks, relationships with medical personnel, familiarity with the medical and insurance systems, and knowledge of other supportive resources.5 However, the recurrence literature has focused primarily on recurrent breast cancer, and to our knowledge it is unknown whether these findings can be generalized more widely or whether resilience persists when patients develop new cancers with different treatment demands.

Because of the dearth of psychosocial research in patients with multiple primary cancers, it is difficult to generate a priori hypotheses regarding the most appropriate outcome assessments in this population. Other authors have suggested that assessment of focused aspects of patient well-being are more likely to identify group differences,8 and we assessed several targeted areas including psychosocial domains in which cancer previously has been shown to have an effect, such as depression, perceived stressfulness, energy level, and sexual functioning. We also postulated that a subsequent primary cancer may have an impact on existential well-being and post-traumatic growth. Standardized questionnaires that have been validated in other cancer patient samples were used to assess these domains, as well as global QOL. We also assessed predictors of QOL, including clinical and treatment variables, sociodemographic variables, and psychologic variables. These psychologic predictors, optimism9 and resilience,10 both demonstrate a stable, trait-like consistency and have been found to positively predict the QOL of cancer patients in previous research.11, 12

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Participants

The population-based Hawaii Tumor Registry (HTR), a member of the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program, was used to identify patients with a history of multiple primary cancers and control patients with a history of a single primary cancer. We drew from all cases in the registry, and study participants were diagnosed between 1964 (when the registry was initiated) and 1999. The registry does not include patients with basal cell or squamous cell skin carcinomas. All surviving patients were eligible for the study if they were proficient in English and residents of Hawaii. Patients with multiple primary cancers were eligible for the study if their second primary cancer diagnosis was made at least 6 months after their initial diagnosis. Patients with multiple primary cancers were matched to single-cancer controls based on disease site (initial diagnosis), age (±10 years), sex, race/ethnicity, time since initial diagnosis (±10 years), and disease stage at initial diagnosis (stages 0–I or stages II–IV according to the American Joint Committee on Cancer and the International Union Against Cancer TNM staging system).

Procedure

All participants were identified via the HTR database. Patients were contacted with the permission of their primary physicians. Participants were sent a mailing including a cover letter explaining the study purpose; a questionnaire packet; and a stamped, self-addressed return envelope, as well as a brochure regarding cancer survivorship resources. After 10 days, reminder postcards were sent to nonrespondents. As a minimal-risk study, written consent was not obtained from each participant; however, the study's cover letter informed participants that returning completed questionnaires implied informed consent. The study's procedure was reviewed and approved by the University of Hawaii Institutional Review Board.

Measures

Demographic and clinical predictors

A self-report form assessed sociodemographics (eg, education, family income, and ethnicity) and clinical data (eg, recurrences and treatments received [such as surgery and chemotherapy]). Information concerning age, types of primary cancers, cancer stage at the time of first diagnosis, and time since first diagnosis was obtained from the HTR.

Comorbidities

Comorbidities were assessed via the Charlson comorbidities index.13 The Charlson comorbidity index is a self-report measure that asks whether patients have experienced any of 19 medical conditions (eg, renal disease or diabetes). For this study, items regarding cancer were eliminated.

Psychologic predictors
Optimism

Optimism was assessed via the 10-item Life Orientation Test (LOT).9 Filler items in the original scale were dropped, resulting in an 8-item scale. Items are assessed on a scale of 0 (Strongly Agree) to 4 (Strongly Disagree), with higher scores representing greater optimism. In the current study, the measure demonstrated good internal consistency (alpha = .78).

Resilience

Resilience was measured with the 25-item Resiliency Scale (RS).10 Items are scored on a 7-point Likert scale with 1 indicating “Disagree” and 7 indicating “Agree” and scored such that higher scores represent greater resilience. Although 5 subscales can be generated from this measure, only the measure's total score was examined. This total score yielded excellent internal consistency (alpha = .95).

Outcome measures
Global QOL

Global QOL was assessed via a single-item measure from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QOQ-C30).14 This item asks patients to rate their “overall quality of life,” and is scored on a 7-point Likert scale, with 1 indicating “Very Poor” and 7 indicating “Excellent.”. Single-item global QOL measures have been shown to compare favorably with longer measures for assessing overall QOL.15, 16

Vitality

Vitality, a measure of subjective energy and vigor, was assessed with the 4-item Medical Outcomes Study Short Form Vitality (MOS-V)17 scale. Items are rated on a 6-point Likert scale with 1 indicating “All of the Time” and 6 indicating “None of the Time.” Higher scores represent more vitality. This measure has been widely used in research with individuals with cancer and has demonstrated good internal consistency in this sample (alpha = .87).

Depressive symptomatology

Depressive symptoms were assessed via the 20-item Center for Epidemiologic Studies-Depression (CES-D) scale.18 Items are scored on a 0-point (Rarely or None of the Time) to 3-point (Most or All of the Time) scale, with higher scores representing greater depressive symptoms. The measure has shown good psychometric properties when used in samples of cancer patients.19, 20 In the current study, the measure yielded good internal consistency (alpha = .88).

Cancer-specific stress

Stressful aspects of the cancer experience were assessed with the 22-item Revised Impact of Event Scale (IES-R).21 This measure yields subscale scores for intrusion and avoidance. Items were scored on a 0-point (Not at All) to 3-point (Often) scale. This measure has been well-validated and widely used with cancer patients, and demonstrated excellent internal consistency in the current study (alpha = .96).

Post-traumatic growth

The 21-item Post-traumatic Growth Inventory (PTGI)22 was used to assess the amount of personal growth perceived as a result of having cancer. Items are rated on a 0-point (I Did Not Experience This Change) to 5-point (I Experienced This Change to a Very Great Degree) Likert scale. The scale has demonstrated reliability in community samples22 and samples of cancer patients.23 In the current study, the measure demonstrated excellent internal consistency (alpha = .98).

Sexual adjustment

Sexual adjustment was measured by a single item adopted from the Sexual Adjustment Questionnaire (SAQ)24 – “Has having cancer changed your sexual relationship with your partner(s)?” This item was rated on 5-point Likert scale with anchors that included “Very bad effect”1 and “Very good effect.”5 Sexual adjustment was only considered for those participants who answered the question and who reported they had a partner (n = 632 participants).

Existential well-being

The 6-item Existential Well-being subscale of the McGill Quality of Life Scale25 was used to measure this construct (eg, “I feel good about myself as a person.”). Items are rated on 11-point Likert scales and scored such that higher scores represent greater existential well-being. In the current study, the measure demonstrated excellent internal consistency (alpha = .90).

Personal and family coping

Patients with multiple primary cancer diagnoses were asked to assess their own and their relatives' ability to cope with their cancer diagnoses with questions reading, “How well were you able to cope with your initial cancer diagnosis?” and, “How well have you been able to cope with having had another cancer diagnosis?” Two equivalent questions were asked regarding the ability of “your family” to cope with the first and subsequent cancer diagnoses. Items were rated on a 1-point (Very Poorly) to 7-point (Very Well) Likert scale. Patients were also asked to compare the difficulty in dealing with the second cancer in comparison with their first diagnosis on a 1-point (Much More Difficult) to 7-point (Much Easier) Likert scale.

Statistical Analysis

Chi-square and 2-sided independent sample Student t tests (t) were used to compare study responders with nonresponders with regard to predictor variables, and participants with multiple primary cancers with single-primary cancer controls with regard to all predictor and outcome measures. For t-test comparisons that showed a significant mean difference between the groups, Cohen d was calculated as a measure of effect size. Hierarchical regression analysis was used to identify variables that predicted QOL outcomes. In the first step, demographic variables, including ethnicity and age, were entered. Clinical variables, including site of the first primary cancer (dummy coded for each of the most prominent disease sites) then were entered into the model. Trait-like psychologic variables (ie, optimism and resilience) were entered into the third step, followed by group membership (control group vs multiple primary cancer group). Correlational analyses were used to examine which factors unique to the multiple primary cancer group (eg, site of second primary cancer) may be related to outcomes of interest.

Finally, 2-sided, dependent-sample Student t tests were used to examine patients' responses on coping items. Patients' reports of their own coping at the time of first diagnosis were compared with their reports of their coping at the second diagnosis. Similar analyses were performed for the families' ability to cope. In addition, the same analytic strategy was used to examine patients' reports of their own coping compared with their families' coping at each time point. A change score was calculated by subtracting the coping score reported for the first cancer diagnosis from the coping score for the second diagnosis, and correlational analysis was used to determine which variables were correlated with changes in perceived ability to cope.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

A total of 1290 patients with multiple primary cancer diagnoses were identified from the HTR. Of these patients, 299 could not be contacted due to out-of-date contact information, 61 were deceased, and 27 had moved out of state. Physicians requested that 15 patients not be contacted and 7 patients were taking part in other studies. The remaining 873 eligible patients were contacted by mail, 487 of whom (55.8%) returned complete surveys. Participants who completed the survey were contacted by telephone to complete missing or unclear data.

The HTR also identified 5015 potential control participants. The pool of potential controls consisted of up to 5 patients matched to each index patient. Contact was attempted with 2662 patients and contact was made with 1497 candidates. Of these, 616 (41.1%) returned completed surveys. Of these 616 patients, 27 had ambiguous information in the HTR regarding their eligibility as controls (eg, a second, but not a first, cancer diagnosis was listed). Data from these 27 patients were eliminated from the study, resulting in a sample of 589 control patients.

Comparisons of demographic and clinical variables obtained from the HTR indicated that individuals who participated in the study were younger (t = 4.72; P < .001; d = −.16) and more likely to have a partner (chi-square = 9.79; P = .002) than those who did not participate. Individuals of Japanese and Chinese ethnicity were relatively more likely to participate compared with individuals of Native Hawaiian and white ethnicity (chi-square = 29.80; P < .001).

Comparison of survivors of multiple primary cancers with control survivors with regard to demographic and clinical variables found that the groups were well-matched, as would be expected based on the matching procedures used (Table 1). No statistically significant differences were found between the 2 groups with regard to any demographic or clinical variable, with the exception of time since the initial cancer diagnosis. However, the difference in time since initial diagnosis of 4.7 years is within the timeframe of ± 10 years used for the matching process.

Table 1. Participant Characteristics
VariableMultiple primary cancers (n = 487)Control (n = 589)
  • SD indicates standard deviation; GED, General Equivilency Diploma.

  • *

    P < .05 between survivor groups.

  • Data missing for 46 multiple primary cancer survivors and 27 control survivors.

  • Data missing for 46 multiple primary cancer survivors and 24 control survivors.

  • §

    Data missing for 44 multiple primary cancer survivors and 25 control survivors.

Age (mean ± SD), y71.3 ± 11.871.4 ± 10.7
Time since first diagnosis (mean ± SD), y*13.6 ± 6.19.9 ± 4.0
Sex, no. (%)
 Female327 (67.1)413 (70.1)
 Male160 (32.9)176 (29.9)
Ethnicity, no. (%)
 White121 (25.0)166 (28.4)
 Chinese37 (7.6)43 (7.4)
 Filipino30 (6.2)35 (6.0)
 Hawaiian35 (7.2)67 (11.4)
 Japanese225 (46.5)250 (42.7)
 Other36 (7.4)24 (4.1)
Relationship status, no. (%)
 With partner315 (71.6)430 (76.6)
 No partner125 (28.4)131 (23.4)
Education, no. (%)
 <High school73 (15.2)63 (10.9)
 High school graduate or GED134 (27.9)152 (26.2)
 Some college140 (29.2)182 (31.4)
 College or university graduate82 (17.1)102 (17.6)
 Postgraduate51 (10.6)81 (14.0)
Income, no. (%)
 < $15,00062 (14.0)61 (11.8)
 $15,000–$24,99979 (17.8)94 (18.3)
 $25,000–$49,999142 (32.0)163 (31.7)
 ≥$50,000161 (36.3)197 (38.3)
Comorbid conditions (mean ± SD)1.3 (1.3)1.3 (1.3)
First primary tumor site, no. (%)
 Breast184 (37.8)258 (43.8)
 Gastrointestinal83 (17.0)102 (17.3)
 Genitourinary66 (13.6)73 (12.4)
 Gynecologic50 (10.3)59 (10.0)
 Skin30 (6.2)38 (6.5)
 Head and neck21 (4.3)16 (2.7)
 Lung16 (3.3)11 (1.9)
 Thyroid14 (2.9)17 (2.9)
 Lymphoma12 (2.5)8 (1.4)
 Other11 (2.3)7 (1.2)
Second primary cancer site, no. (%)
 Breast203 (41.8)
 Genitourinary91 (18.7)
 Gastrointestinal73 (15.0)
 Gynecologic32 (6.6)
 Skin29 (6.0)
 Head and neck20 (4.2)
 Lung13 (2.7)
 Thyroid11 (2.3)
 Lymphoma7 (1.5)
 Other7 (1.5)
Treatments for first primary tumor, no. (%)
 Surgery389 (87.8)515 (91.3)
 Chemotherapy387 (87.8)478 (85.1)
 Radiotherapy§327 (74.2)407 (72.0)

Among those with distant disease, 15 control patients (2.5%) and 17 patients with multiple primary cancers (3.5%) had survived a stage IV diagnosis according to the TNM system. The most common cancer diagnosis for both groups was breast cancer. Breast cancer was also found to be the most common second cancer diagnosis for those individuals with multiple malignancies. A low number of comorbid conditions was found, which is consistent with previous literature in samples of older cancer patients.26

Two-sided independent sample Student t tests were used to compare the groups with regard to QOL measures. The t-values may be found in Table 2. Survivors of multiple primary cancers reported lower global QOL (Cohen d = .38), lower vitality scores (d = .17), higher total stress (d = .14), and lower existential well-being (d = .18). With regard to specific aspects of stress, neither subscale of the IES was found to be statistically significant, although both the IES-Intrusion subscale (d = .12) and the IES-Avoidance subscale (d = .13) demonstrated marginally significant results (Ps ≤ .07). No significant differences were found with regard to measures of post-traumatic growth, depressive symptomatology, and changes in sexual relationships.

Table 2. Mean Scores in Multiple Primary Cancer and Control Survivors
VariableMultiple primary cancersControlt value
  • t value indicates 2-sided independent sample Student t test; QOL, quality of life; MOS-Vitality, Medical Outcomes Study Short Form Vitality subscale; CES-D, Center for Epidemiologic Studies-Depression; IES, Impact of Events Scale; IES-A, Impact of Events Scale Avoidance subscale; IES-I, Impact of Events Scale Intrusiveness subscale; PTGI, Posttraumatic Growth Inventory; SAQ: Sexual Attitudes Questionnaire.

  • *

    P ≤ .001.

  • P ≤ 01

  • P ≤ .05.

Global QOL5.6 (1.2)6.0 (1.0)5.42*
MOS-Vitality59.3 (20.8)62.4 (19.4)2.41
CES-D11.7 (7.6)11.6 (7.4)−1.07
IES-Total12.0 (14.1)10.0 (13.9)−1.93
IES-A6.6 (8.3)5.5 (8.1)−1.78
IES-I5.4 (6.7)4.5 (6.4)−1.89
McGill-Existential8.5 (1.5)8.7 (1.3)2.78
PTGI66.9 (32.5)65.0 (33.9)−0.95
SAQ-Relationship change2.7 (0.7)2.8 (0.7).24

Hierarchical regression analysis was used to identify predictors of QOL outcomes (Table 3). In the first step, sociodemographic variables were found to significantly predict all outcomes. Clinical variables, entered in the second step, were found to predict all variables except existential well-being. The third step (dispositional optimism and dispositional resilience) explained significant variances in all outcomes except post-traumatic growth. Finally, survivor group (multiple primary cancer vs single primary cancer) was found to be predictive of remaining variances in global QOL, vitality, and existential well-being. The variance accounted for by group membership on global QOL (coefficient of determination [R2] = .04) falls in between a small and medium effect size according to Cohen's rule of thumb,27 whereas the variance accounted for by group membership with regard to vitality and existential well-being yielded a small effect. Individual predictors that were found to remain significant after all variables were entered into each regression model are reported in Table 4. Trait resilience predicted unique variance in all outcome variables, except for post-traumatic growth. Similarly, dispositional optimism predicted unique variance in all outcome variables except post-traumatic growth and changes in sexual relationships.

Table 3. Change In Adjusted R2 Values For Stepwise Hierarchical Regressions
Outcome variableStep 1*Step 2Step 3Step 4§Total adj. R2
  • R2 indicates coefficient of determination; QOL, quality of life; MOS-Vitality, Medical Outcomes Study Short Form Vitality subscale; CES-D, Center for Epidemiologic Studies-Depression; IES, Impact of Events Scale; PTGI, Posttraumatic Growth Inventory; SAQ: Sexual Attitudes Questionnaire.

  • *

    Step 1 predictors: age, sex, ethnicity (white vs Chinese vs Filipino vs Hawaiian vs Japanese vs other), partner status (partnered vs not partnered), income, and education.

  • Step 2 predictors: site of first primary tumor (head and neck vs gastrointestinal vs lung vs skin vs breast vs gynecologic vs prostate vs thyroid vs lymphoma vs other), stage of first primary tumor, first diagnosis date, surgery, chemotherapy, radiotherapy, and number of comorbidities.

  • Step 3 predictors: Life Orientation Test and Resiliency Scale.

  • §

    Step 4 predictors: survivor group (multiple primaries vs control).

  • P ≤ .001.

  • P ≤ .05.

  • #

    P ≤ .01.

Global QOL0.030.040.130.040.24
MOS-Vitality0.010.090.100.010.21
CES-D0.050.02#0.010.000.09
IES-Total0.030.030.02#0.000.08
McGill-Existential0.070.000.300.010.38
PTGI0.100.02#0.000.000.12
SAQ-Relationship change0.010.030.010.000.06
Table 4. Statistically Significant Predictors in Multilevel Regressions
Outcome variablePredictorbetatP
  1. t value indicates 2-sided independent sample Student t test; QOL, quality of life; MOS-Vitality, Medical Outcomes Study Short Form Vitality subscale; CES-D, Center for Epidemiologic Studies-Depression; IES, Impact of Events Scale; PTGI, Posttraumatic Growth Inventory; SAQ: Sexual Attitudes Questionnaire.

  2. Only statistically significant (P < .05) predictors in Step 4 are shown. Filipino is a dummy-coded variable with non-Filipino as the control group. Sex is coded as 0 for male and 1 for female. Partner is a dummy-coded variable with No partner as the control group. Disease site variables, including Head and neck, Gastrointestinal, Skin, Breast, Genitourinary, Thyroid, and Lymphoma, are each dummy-coded variables with 1 for the respective disease site and 0 for all other sites. Radiotherapy is coded as 0 if radiotherapy was not received and 1 if it was received. Group is coded as 0 for control patients and 1 for multiple primary tumor patients. All other variables were measured on linear scales.

Global QOLAge.082.06.04
Income.102.84.005
Comorbidities−.16−5.13< .001
Optimism.154.29< .001
Resilience.288.52< .001
Survivor group−.20−6.39< .001
MOS-VitalityAge.082.15.03
Lymphoma.082.16.03
Comorbidities−.27−8.34< .001
Optimism.174.68< .001
Resilience.226.44< .001
Survivor group−.08−2.51.01
CES-DAge−.13−3.63< .001
Sex.173.08.002
Head and neck−.10−2.34.02
Gastrointestinal−.12−1.99.05
Breast−.23−2.75.006
Gynecologic−.13−2.32.02
Radiotherapy.082.09.04
Comorbidities.143.87< .001
Optimism−.09−2.37.02
Resilience−.08−2.09.04
IESAge−.12−2.87.004
Filipino ethnicity.132.93.004
Sex.122.21.03
Head and neck−.12−2.85.004
Gastrointestinal−.16−2.73.006
Skin−.11−2.31.02
Breast−.29−3.51< .001
Gynecologic−.20−3.50< .001
Genitourinary−.14−2.81.005
Thyroid−.13−3.19.002
Lymphoma−.15−3.66< .001
Comorbidities.082.31.02
Optimism−.10−2.83.008
Resilience−.10−3.04.005
McGill-ExistentialAge.092.54.01
White ethnicity−.11−2.03.04
Income.102.95.003
Sex.224.83< .001
Partner.072.31.02
Optimism.134.09< .001
Resilience.5016.74< .001
Survivor group−.07−2.60.01
PTGIAge−.28−6.92< .001
SAQ-Relationship changeSex.183.27.001
Head and neck−.08−2.00.05
Comorbidities.092.54.01
Resilience.112.34.02

Finally, patients who had experienced multiple primary cancers were asked to rate how well they and their families coped with each cancer diagnosis. Patients reported that they coped better than their families with both diagnoses, and that coping with the second diagnosis was easier than with the first for both parties (Table 5). Correlational analysis indicated that individuals whose first cancer was a genitourinary cancer (including prostate cancer) were more likely to state that the first cancer was easier to cope with for both themselves (r = –.11; P = .02) and their families (r = –.17; P < .001). Skin cancer (melanoma) as a second diagnosis was easier to cope with for both patients (r = .11; P < .01) and their families (r = .09; P = .05).

Table 5. Coping With Initial and Second Cancer Diagnoses: Survivors' Perceptions of Themselves and Their Families
 SelfFamily
  1. Items were rated on a 7-point Likert scale, with higher scores indicating better coping. Items not sharing an asterisk (*) differ at P ≤ .01.

First cancer4.74 + 1.94*4.55 + 1.87
Second cancer4.96 + 1.804.78 + 1.82*

Scores on a single continuous scale questioning the relative difficulty of dealing with their first 2 cancer diagnoses indicated that the average patient marked the 7-point scale slightly better than the midpoint, indicating that it was a little easier to deal with the second cancer diagnosis (mean [m] = 4.8; standard deviation [SD] = 2.0). Individuals who scored higher with regard to resilience more strongly stated that the second cancer was easier to cope with (r = .12; P = .01).

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Individuals in the current study who survived > 1 cancer diagnosis experienced modest, but lasting, decrements in overall QOL. Findings suggest that survivors of multiple primary cancers experience reduced functioning in several psychosocial domains, including global QOL, vitality, cancer-specific stress reactions, and existential well-being, but the small effect sizes may indicate that these differences may not be clinically relevant for the majority of patients, especially when demographic, clinical, and trait-like psychosocial variables such as optimism are taken into account.

From a clinical perspective, survivors of multiple primary cancers compared favorably with those who experienced a single malignancy. Indeed, the overall global QOL ratings were nearly 6 on a 7-point Likert scale. Although patients with multiple primary diagnoses did demonstrate significantly lower QOL scores than control participants, scores for this group still approached the measure's ceiling.

The results of the current study are comparable to findings from previous studies of the psychosocial impact of cancer recurrence.5, 6 Those studies showed that, particularly among patients with recurrent breast cancer, most patients demonstrate resilient psychologic functioning. The results of the current study suggest that both men and women with a variety of cancer diagnoses tend to respond resiliently when faced with another cancer. This resilience was found equally among individuals of both genders, all ethnic groups, and regardless of cancer type at either diagnosis.

However, this report of resilience is tempered by the finding that the QOL deficits reported by these survivors were identified nearly a decade after the average patient's most recent diagnosis. Differences in cancer-specific stress were still detectable, as has been seen in patients with recurrent breast cancer.5, 7 The experience of cancer can have long-term effects, and the experience of multiple cancers may add to this risk.

In terms of protective factors, the current study supports the findings of earlier reports with regard to the beneficial aspects of optimism and resilience for cancer survivors. These variables explained more of the variance noted in the majority of the outcome measures in the current study than any other predictor. These findings are especially meaningful in light of research that suggests that optimism levels may be influenced by psychologic intervention, particularly among patients who score lower in optimism.28

However, it should be noted that, for many of the outcomes measured herein, the variance explained by predictor variables was low, despite the relatively large set of predictors used. The low amounts of explained variance suggest that unmeasured variables contribute to patients' QOL. Notably, although an ethnically diverse population was sampled, only a single variable demonstrated a correlation with ethnicity, with Filipino survivors found to have more cancer-related stress symptoms. Variables that went unmeasured in the current study and that may correlate with QOL include neuroticism,29 coping styles,30 physical activity levels,31 and the presence of persistent fatigue.32

Because the current study utilized a cross-sectional design, the trajectory of change in the patients' QOL is unclear. Likewise, this study was not able to assess how patients respond immediately after the diagnosis of a second primary cancer, when it is likely that patients experience greater QOL deficits. If so, factors that might lead to faster or slower recovery of functioning could not be identified here.

Another limitation of the current study is its focus on individuals who have survived their cancer diagnoses and whose cancer(s) are now in remission. Although the recurrence literature suggests that patients demonstrate psychologic resilience even when the recurrence is deemed incurable,5 other studies have found significant QOL deficits in patients with more serious disease.7, 33 Among patients with multiple primary cancer diagnoses, important psychosocial differences may exist between individuals with a more survivable second primary diagnosis versus those whose second primary cancer results in a worse prognosis.

Additional limitations of the current study include the geographically and culturally distinct residence of study participants, and differences between study responders and nonresponders, including age and ethnicity. Although the response rate noted in the current study was comparable to or surpassed that of other tumor registry-based studies,34–36 nonresponders may have differed from the current study sample in unknown ways. In addition, patients with multiple primary tumors responded to the study at a higher rate than control patients, which may have introduced additional error into the study.

Nevertheless, the current study has important strengths, including a population-based sample with both genders and diverse ethnicities and cancer sites, a case-control design that matched groups on a number of important variables, and a sample size that permitted the detection of small differences between the multiple primary cancer and control groups. To our knowledge, no other study to date has examined the psychosocial characteristics of this important group of cancer patients, and as such it begins to address an important gap in the psychosocial oncology literature. Studies designed to follow the course of patients' psychosocial functioning and QOL from the time they receive a second primary cancer diagnosis may be particularly useful. Likewise, the heterogeneity of the sample in the current study may obscure QOL consequences experienced by those who are diagnosed with specific cancer combinations. For example, a survivor of prostate cancer may not be entirely prepared for the specific consequences of a later head and neck cancer, such as disfigurement, eating difficulties, or voice changes.

Overall, the results of the current study suggest that health professionals should attend to the QOL needs of patients with multiple primary cancer diagnoses in a fashion similar to that for those with a single cancer diagnosis. Concerned patients could be reassured that surviving a second cancer diagnosis does not appear to result in large decrements in QOL and well-being for most patients.

Acknowledgements

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

We appreciate the assistance of Marc Goodman, Amy Krambrink, Marya Levintova, Lynne Wilkens, Michael Green, and Sarah Gibbons Stein.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES
  • 1
    CurtisRE,FreedmanDM,RonE, et al., editors. New Malignancies Among Cancer Survivors: SEER Cancer Registries, 1973–2000. NIH Pub. No. 05-5302. Bethesda, MD: National Cancer Institute; 2006.
  • 2
    Ahsan H,Neugut AI. Radiation therapy for breast cancer and increased risk for esophageal carcinoma. Ann Intern Med. 1998; 128: 114117.
  • 3
    Rheingold SR,Neugut AI,Meadows AT. Secondary cancers: incidence, risk factors, and management. In: KufeDW,PollockRE,WeichselbaumRR, et al., editors. Cancer Medicine.6th ed. Hamilton, Ontario, Canada: BC Decker; 2003: 26232631.
  • 4
    Travis LB. The epidemiology of second primary cancers. Cancer Epidemiol Biomarkers Prev. 2006; 15: 20202026.
  • 5
    Andersen BL,Shapiro CL,Farrar WB,Crespin T,Wells-Digregorio S. Psychological responses to cancer recurrence. Cancer. 2005; 104: 15401547.
  • 6
    Munkres A,Oberst MT,Hughes SH. Appraisal of illness, symptom distress, self-care burden, and mood states in patients receiving chemotherapy for initial and recurrent cancer. Oncol Nurs Forum. 1992; 19: 12011209.
  • 7
    Oh S,Heflin L,Meyerowitz BE,Desmond KA,Rowland JH,Ganz PA. Quality of life of breast cancer survivors after a recurrence: a follow-up study. Breast Cancer Res Treat. 2004; 87: 4557.
  • 8
    Ganz PA,Goodwin PJ. Quality of life in breast cancer: what have we learned and where do we go from here? In: LipscombJ,GotayCC,SnyderC, editors. Outcomes Assessment in Cancer: Measures, Methods and Applications. Cambridge, U.K.: Cambridge University Press; 2005: 93125.
  • 9
    Scheier MF,Carver CS. Optimism, coping, and health: assessment and implications of generalized outcome expectancies. Health Psychol. 1985; 4: 219247.
  • 10
    Wagnild GM,Young HM. Development and psychometric evaluation of the Resilience Scale. J Nurs Meas. 1993; 1: 165178.
  • 11
    Carver CS,Pozo C,Harris SD, et al. How coping mediates the effect of optimism on distress: a study of women with early stage breast cancer. J Pers Soc Psychol. 1993; 65: 375390.
  • 12
    Gotay CC,Isaacs P,Pagano I. Quality of life in patients who survive a dire prognosis compared to control cancer survivors. Psychooncology. 2004; 13: 882892.
  • 13
    Charlson ME,Pompei P,Ales KL,MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987; 40: 373383.
  • 14
    Aaronson NK,Ahmedzai S,Bergman B, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993; 85: 365376.
  • 15
    Bernhard J,Sullivan M,Hurny C,Coates AS,Rudenstam CM. Clinical relevance of single item quality of life indicators in cancer clinical trials. Br J Cancer. 2001; 84: 11561165.
  • 16
    de Boer AG,van Lanschot JJ,Stalmeier PF, et al. Is a single-item visual analogue scale as valid, reliable and responsive as multi-item scales in measuring quality of life? Qual Life Res. 2004; 13: 311320.
  • 17
    Ware JEJr,Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992; 30: 473483.
  • 18
    Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Measure. 1977; 1: 385401.
  • 19
    Beeber LS,Shea J,McCorkle R. The Center for Epidemiologic Studies Depression Scale as a measure of depressive symptoms in newly diagnosed patients. J Psychosoc Oncol. 1998; 16: 120.
  • 20
    Hann D,Winter K,Jacobsen P. Measurement of depressive symptoms in cancer patients: evaluation of the Center for Epidemiological Studies Depression Scale (CES-D). J Psychosom Res. 1999; 46: 437443.
  • 21
    Weiss D,Marmar C. The Impact of Events Scale-Revised. In: WilsonJ,KeaneT, editors. Assessing Psychological Trauma and PTSD. New York: Guildford; 1997: 399411.
  • 22
    Tedeschi RG,Calhoun LG. The Posttraumatic Growth Inventory: measuring the positive legacy of trauma. J Trauma Stress. 1996; 9: 455471.
  • 23
    Widows MR,Jacobsen PB,Booth-Jones M,Fields KK. Predictors of posttraumatic growth following bone marrow transplantation for cancer. Health Psychol. 2005; 24: 266273.
  • 24
    Waterhouse J,Metcalfe MC. Development of the sexual adjustment questionnaire. Oncol Nurs Forum. 1986; 13: 5359.
  • 25
    Cohen SR,Mount BM,Tomas JJ,Mount LF. Existential well-being is an important determinant of quality of life. Evidence from the McGill Quality of Life Questionnaire. Cancer. 1996; 77: 576586.
  • 26
    Extermann M. Measuring comorbidity in older cancer patients. Eur J Cancer. 2000; 36: 453471.
  • 27
    Cohen J. Statistical Power Analysis for the Behavioral Sciences ( 2nd ed.). Hillsdale, NJ: Erlbaum; 1988.
  • 28
    Antoni MH,Lehman JM,Kilbourn KM, et al. Cognitive-behavioral stress management intervention decreases the prevalence of depression and enhances benefit finding among women under treatment for early-stage breast cancer. Health Psychol. 2001; 20: 2032.
  • 29
    Aarstad HJ,Aarstad AK,Birkhaug EJ,Bru E,Olofsson J. The personality and quality of life in HNSCC patients following treatment. Eur J Cancer. 2003; 39: 18521860.
  • 30
    Ransom S,Jacobsen PB,Schmidt JE,Andrykowski MA. Relationship of problem-focused coping strategies to changes in quality of life following treatment for early stage breast cancer. J Pain Symptom Manage. 2005; 30: 243253.
  • 31
    Alfano CM,Rowland JH. Recovery issues in cancer survivorship: a new challenge for supportive care. Cancer J. 2006; 12: 432443.
  • 32
    Arndt V,Stegmaier C,Ziegler H,Brenner H. A population-based study of the impact of specific symptoms on quality of life in women with breast cancer 1 year after diagnosis. Cancer. 2006; 107: 24962503.
  • 33
    Gotay CC,Moinpour CM,Unger JM, et al. Impact of a peer-delivered telephone intervention for women experiencing a breast cancer recurrence. J Clin Oncol. 2007; 25: 20932099.
  • 34
    Pakilit AT,Kahn BA,Petersen L,Abraham LS,Greendale GA,Ganz PA. Making effective use of tumor registries for cancer survivorship research. Cancer. 2001; 92: 13051314.
  • 35
    Potosky AL,Knopf K,Clegg LX, et al. Quality-of-life outcomes after primary androgen deprivation therapy: results from the Prostate Cancer Outcomes Study. J Clin Oncol. 2001; 19: 37503757.
  • 36
    Ramsey SD,Andersen MR,Etzioni R, et al. Quality of life in survivors of colorectal carcinoma. Cancer. 2000; 88: 12941303.